Quantile mapping technique for enhancing satellite-derived precipitation data in hydrological modelling: a case study of the Lam River Basin, Vietnam DOI Creative Commons

Nhu Y. Nguyen,

Trần Ngọc Anh, Huu Duy Nguyen

et al.

Journal of Hydroinformatics, Journal Year: 2024, Volume and Issue: 26(8), P. 2026 - 2044

Published: July 24, 2024

ABSTRACT Accurate precipitation is crucial for hydrological modelling in sparse gauge regions like the Lam River Basin (LRB) Vietnam. Gridded data from satellite and numerical models offer significant advantages such areas. However, estimates (SPEs) are subject to uncertainties, especially high variable of topography precipitation. This study focuses on enhancing accuracy Integrated Multi-satellitE Retrievals Global Precipitation Measurement (IMERG), Climate Prediction Center morphing technique (CMORPH) using Quantile Mapping (QM) technique, aligning cumulative distribution functions observed with those SPEs, assessing impact predictions. The highlights that post-correction IMERG QM performs better than other sets, model's performance LRB at different temporal scales. Nash–Sutcliffe efficiency values increased 0.60 0.77, surpassing original IMERG's 0.52 0.74, correlation coefficients improved 0.79 0.89 (compared previous 0.75–0.86) modelling. Additionally, Percent Bias (PBIAS) decreased approximately −1.66 −2.21% (contrasting initial −20.22 4.6%) corrected SPEs. These findings have implications water resource management disaster risk reduction initiatives Vietnam countries.

Language: Английский

Evaluating rainfall erosivity on the Tibetan Plateau by integrating high spatiotemporal resolution gridded precipitation and gauge data DOI

Bing Yin,

Yun Xie, Chong Yao

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 947, P. 174334 - 174334

Published: June 30, 2024

Language: Английский

Citations

1
Quantile mapping technique for enhancing satellite-derived precipitation data in hydrological modelling: a case study of the Lam River Basin, Vietnam DOI Creative Commons

Nhu Y. Nguyen,

Trần Ngọc Anh, Huu Duy Nguyen

et al.

Journal of Hydroinformatics, Journal Year: 2024, Volume and Issue: 26(8), P. 2026 - 2044

Published: July 24, 2024

ABSTRACT Accurate precipitation is crucial for hydrological modelling in sparse gauge regions like the Lam River Basin (LRB) Vietnam. Gridded data from satellite and numerical models offer significant advantages such areas. However, estimates (SPEs) are subject to uncertainties, especially high variable of topography precipitation. This study focuses on enhancing accuracy Integrated Multi-satellitE Retrievals Global Precipitation Measurement (IMERG), Climate Prediction Center morphing technique (CMORPH) using Quantile Mapping (QM) technique, aligning cumulative distribution functions observed with those SPEs, assessing impact predictions. The highlights that post-correction IMERG QM performs better than other sets, model's performance LRB at different temporal scales. Nash–Sutcliffe efficiency values increased 0.60 0.77, surpassing original IMERG's 0.52 0.74, correlation coefficients improved 0.79 0.89 (compared previous 0.75–0.86) modelling. Additionally, Percent Bias (PBIAS) decreased approximately −1.66 −2.21% (contrasting initial −20.22 4.6%) corrected SPEs. These findings have implications water resource management disaster risk reduction initiatives Vietnam countries.

Language: Английский

Citations

1